code: def test_hific_encoder_forward(
      latent_features: int,
      hyper_features: int,
      num_residual_blocks: int,
      arange_4d_image: Tensor,
  ):
      model = HiFiCAutoencoder(
          in_channels=arange_4d_image.shape[1],
          latent_features=latent_features,
          hyper_features=hyper_features,
          num_residual_blocks=num_residual_blocks,
      )
  
      output = model(arange_4d_image)
  
      assert output.image.shape == arange_4d_image.shape
  
file_path: NeuralCompression/tests/models/test_hific_autoencoder.py
imports: import pytest
  import torch
  from torch import Tensor
  from neuralcompression.models import HiFiCAutoencoder
label_desc: Use image node_id 1 for calling a global function with example usage: test_hific_encoder_forward(latent_features, hyper_features, num_residual_blocks, arange_4d_image) without return types